Product Intern

São Paulo

Comp is a Series A startup that combines AI and deep HR expertise to help companies attract, retain, and manage people through products across different areas of HR. We are backed by leading VCs including Khosla Ventures (Keith Rabois) and Kaszek (first investors in Nubank).

On Comp's product team, you own products end to end, whether that's a tool our own team relies on every day or a product customers use to run their People function, and you build them to fundamentally change how work gets done. You work at the intersection of HR expertise, product, engineering, and AI, going deep on the problem: how the work happens today, who does it, where it breaks, and why it's done that way at all. Then you build the answer, whether that's a workflow, an agent, a skill, a module, or an entire product.

Your ultimate goal is to create products that give people leverage they didn't have before. Work that used to take weeks should take minutes, and decisions that used to depend on a few experts should be within reach of anyone who needs to make them.

Your product will be Benchmark, Comp's salary survey. Companies share their teams' compensation data and, in return, get access to a platform with information on what the market pays by role and by level, including salaries, bonuses and benefits. We are making every Comp product AI-native, and for Benchmark that means making the whole experience smarter: simplifying how data is submitted and validated, making it easier to resolve users' questions, and generating insights from the patterns and inconsistencies found across the dataset as a whole. That vision is still being built.

We are looking for someone who identifies the opportunities, develops the solutions, and turns ideas into concrete improvements for the product and for the people who use it. That is why this role exists, and you will own Benchmark end to end: from the quality of the data coming in, to how clients and internal teams use it, to how the product evolves.

What you'll do

Validate every dataset submitted by companies before it is incorporated into Benchmark, making sure the data is complete, the salaries are coherent and there are no gaps.
Support clients and answer their questions throughout the submission process, from filling in the spreadsheet to having the data approved on the platform.
Serve internal teams when they need a specific cut of the dataset, by role, sector or country, and build ways for them to access that information on their own.
Analyze the dataset as a whole and identify patterns and inconsistencies that do not surface when cases are looked at one at a time.
Propose and implement product improvements, both for the people submitting data and for the people using it.

Desired profile

We are flexible on background and prior experience, but we are looking for someone who:

Has a critical eye for data. Identifies values outside the expected range, recognizes inconsistencies and investigates what caused them.
Uses AI as leverage. Faced with a new problem, explores solutions with AI, weighs the alternatives and moves forward independently.
Makes progress without having every answer. Seeks context, forms hypotheses and learns along the way. When help is needed, brings in the right people with a clear account of the problem.
Documents and communicates clearly. Records what they learn so the knowledge stays accessible and can be applied by other people.
Puts themselves in the client's shoes. Understands what clients struggle with and carries that perspective into every reply and every product improvement.
Is interested in data. Prior exposure can come from an internship, an academic project or something self-started. What matters more is the curiosity to understand how a dataset is structured, what makes data trustworthy and which tool fits which problem.
Is interested in product. Understands the problem before jumping to the solution, observes how people use the product, tests hypotheses and follows the impact of each change on the user experience.

Prior knowledge of data or product is valued, but not required. What matters most is the drive to learn fast and put the behaviors described above into practice.

Compensation

P75 of market Total Cash compensation (based on candidate seniority) + the opportunity to earn very significant equity in Comp and become a partner over time.

Hiring process

Intro call

30 minutes

Deep-dive interviews

2–3 sessions of 45 minutes

Case Study

Practical challenge

Reference checks

Conversations with former managers/peers

Offer

Final proposal

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